基于二次谱的直扩信号伪码周期估计方法研究

Zhenyu Teng, Xinxin Geng,Fan Zhou,Yongxin Feng

数码世界（2016）

Cited 2|Views5

Abstract

文章采用二次功率谱法实现直接序列扩频信号(DS/SS信号)伪码周期的估计,此方法是对接收信号求得一次功率谱后再进行第二次求功率谱处理,最终得到信号的二次谱在信号伪码周期整数倍处出现一系列的尖峰脉冲,脉冲间距即为伪码周期.通过对二次谱法进行仿真实验,结果表明在较低信噪比条件下能够实现直扩信号的伪码周期估计;准确估计时所需的信噪比容限随着伪码周期的增加而逐渐降低.

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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